PEFT/diffusion

1{2 "cells": [3  {4   "cell_type": "markdown",5   "id": "acd7b15e",6   "metadata": {},7   "source": [8    "# Dreambooth with OFT\n",9    "This Notebook assumes that you already ran the train_dreambooth.py script to create your own adapter."10   ]11  },12  {13   "cell_type": "code",14   "execution_count": null,15   "id": "acab479f",16   "metadata": {},17   "outputs": [],18   "source": [19    "from diffusers import DiffusionPipeline\n",20    "from diffusers.utils import check_min_version, get_logger\n",21    "from peft import PeftModel\n",22    "\n",23    "# Will error if the minimal version of diffusers is not installed. Remove at your own risks.\n",24    "check_min_version(\"0.10.0.dev0\")\n",25    "\n",26    "logger = get_logger(__name__)\n",27    "\n",28    "BASE_MODEL_NAME = \"stabilityai/stable-diffusion-2-1-base\"\n",29    "ADAPTER_MODEL_PATH = \"INSERT MODEL PATH HERE\""30   ]31  },32  {33   "cell_type": "code",34   "execution_count": null,35   "metadata": {},36   "outputs": [],37   "source": [38    "pipe = DiffusionPipeline.from_pretrained(\n",39    "    BASE_MODEL_NAME,\n",40    ")\n",41    "pipe.to(\"cuda\")\n",42    "pipe.unet = PeftModel.from_pretrained(pipe.unet, ADAPTER_MODEL_PATH + \"/unet\", adapter_name=\"default\")\n",43    "pipe.text_encoder = PeftModel.from_pretrained(\n",44    "    pipe.text_encoder, ADAPTER_MODEL_PATH + \"/text_encoder\", adapter_name=\"default\"\n",45    ")"46   ]47  },48  {49   "cell_type": "code",50   "execution_count": null,51   "metadata": {},52   "outputs": [],53   "source": [54    "prompt = \"A photo of a sks dog\"\n",55    "image = pipe(\n",56    "    prompt,\n",57    "    num_inference_steps=50,\n",58    "    height=512,\n",59    "    width=512,\n",60    ").images[0]\n",61    "image"62   ]63  }64 ],65 "metadata": {66  "kernelspec": {67   "display_name": "Python 3 (ipykernel)",68   "language": "python",69   "name": "python3"70  },71  "language_info": {72   "codemirror_mode": {73    "name": "ipython",74    "version": 375   },76   "file_extension": ".py",77   "mimetype": "text/x-python",78   "name": "python",79   "nbconvert_exporter": "python",80   "pygments_lexer": "ipython3",81   "version": "3.10.11"82  },83  "vscode": {84   "interpreter": {85    "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"86   }87  }88 },89 "nbformat": 4,90 "nbformat_minor": 591}92